Apptest.ai simplifies automated testing for device-to-device interaction flows—no scripting, no manual setup, and no emulators required.
Circumventing the Limits of Autonomous Exploratory Testing: Maximizing Test Coverage with Test Path Adjustment
🔍 Reveal more hidden defects by Autonomous Test Path Adjustment Apptest.ai’s Autonomous Exploratory Testing allows AI to actively explore various pages within an app, detecting unexpected issues such as force closures (FC) and application not responding (ANR)—all without the need for predefined test cases or manual automation setups. However, this approach has some inherent limitations.
AI Testbot: Transform Your QA with Zero-Touch Automation
The paradigm of mobile app test automation is rapidly evolving. AI Testbot combines precise user behavior simulation with advanced AI analytics to effectively validate application stability. This innovative approach is fundamentally transforming QA processes across the industry. 🔍 Core Technologies in Intelligent Test Automation 👥 User-Based Test Execution The cornerstone of test automation lies in […]
The Future of AI App Testing: 2,000 Bugs Uncovered
“Overtime QA? With AI, those days are over.” Apptest.ai’s AI-powered automation is transforming app testing for global enterprises, eliminating manual effort and redefining quality assurance. Why QA Teams Love AI App Testing “We automated without developers—AI made it simple.”“It tests apps like real users and finds issues we missed.”“No more endless script maintenance—AI adapts automatically.” […]
What is Automation Testing?
Automation testing for mobile apps is a way of testing apps in which software tools are used to automate the process of executing test cases. Software developers do this to ensure that the app functions as intended and to identify any bugs or issues that need to be fixed. When it comes to mobile app […]
The Five Levels of AI Automation
As AI increasingly dominates headlines, it’s important to highlight the differences in AI capabilities. One of the earliest uses of a five-level classification system for AI came from the self-driving car industry. This method of distinguishing capabilities also provides a road map for understanding how much more there is to achieve with AI. In 2014, […]
Exploratory Testing Fundamentals: Can AI Revive This Unpopular Approach?
Quality assurance (QA) ensures that software performs as intended, typically using two main approaches: top-down (functional testing) and bottom-up (exploratory testing). Functional testing focuses on predefined scenarios, while exploratory testing—less common—simulates real-world usage patterns without set scripts. The latter faces challenges due to the difficulty in navigating all possible user paths. However, AI has begun transforming exploratory testing. […]
Top 5 Types of Mobile App Bugs Found Using AI
With over 1,000 new mobile apps launching every day, maintaining app quality is becoming a significant challenge for developers. Mobile app errors not only disrupt user experience but also lead to poor app ratings and potential uninstalls. The current mobile app error rate hovers around 15%, emphasizing the need for advanced and scalable testing solutions. Thanks […]